292 research outputs found
Privacy and Confidentiality in an e-Commerce World: Data Mining, Data Warehousing, Matching and Disclosure Limitation
The growing expanse of e-commerce and the widespread availability of online
databases raise many fears regarding loss of privacy and many statistical
challenges. Even with encryption and other nominal forms of protection for
individual databases, we still need to protect against the violation of privacy
through linkages across multiple databases. These issues parallel those that
have arisen and received some attention in the context of homeland security.
Following the events of September 11, 2001, there has been heightened attention
in the United States and elsewhere to the use of multiple government and
private databases for the identification of possible perpetrators of future
attacks, as well as an unprecedented expansion of federal government data
mining activities, many involving databases containing personal information. We
present an overview of some proposals that have surfaced for the search of
multiple databases which supposedly do not compromise possible pledges of
confidentiality to the individuals whose data are included. We also explore
their link to the related literature on privacy-preserving data mining. In
particular, we focus on the matching problem across databases and the concept
of ``selective revelation'' and their confidentiality implications.Comment: Published at http://dx.doi.org/10.1214/088342306000000240 in the
Statistical Science (http://www.imstat.org/sts/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Comment: Complex Causal Questions Require Careful Model Formulation: Discussion of Rubin on Experiments with "Censoring" Due to Death
Comment on Complex Causal Questions Require Careful Model Formulation:
Discussion of Rubin on Experiments with ``Censoring'' Due to Death
[math.ST/0612783]Comment: Published at http://dx.doi.org/10.1214/088342306000000295 in the
Statistical Science (http://www.imstat.org/sts/) by the Institute of
Mathematical Statistics (http://www.imstat.org
William Kruskal: My Scholarly and Scientific Model
Discussion of ``The William Kruskal Legacy: 1919--2005'' by Stephen E.
Fienberg, Stephen M. Stigler and Judith M. Tanur [arXiv:0710.5063]Comment: Published in at http://dx.doi.org/10.1214/088342306000000376 the
Statistical Science (http://www.imstat.org/sts/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Introduction to papers on the modeling and analysis of network data
Introduction to papers on the modeling and analysis of network dataComment: Published in at http://dx.doi.org/10.1214/10-AOAS346 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Editorial: Statistics and forensic science
Forensic science is usually taken to mean the application of a broad spectrum
of scientific tools to answer questions of interest to the legal system.
Despite such popular television series as CSI: Crime Scene Investigation and
its spinoffs--CSI: Miami and CSI: New York--on which the forensic scientists
use the latest high-tech scientific tools to identify the perpetrator of a
crime and always in under an hour, forensic science is under assault, in the
public media, popular magazines [Talbot (2007), Toobin (2007)] and in the
scientific literature [Kennedy (2003), Saks and Koehler (2005)]. Ironically,
this growing controversy over forensic science has occurred precisely at the
time that DNA evidence has become the ``gold standard'' in the courts, leading
to the overturning of hundreds of convictions many of which were based on
clearly less credible forensic evidence, including eyewitness testimony [Berger
(2006)].Comment: Published in at http://dx.doi.org/10.1214/07-AOAS140 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Editorial: Statistics and "The lost tomb of Jesus"
What makes a problem suitable for statistical analysis? Are historical and
religious questions addressable using statistical calculations? Such issues
have long been debated in the statistical community and statisticians and
others have used historical information and texts to analyze such questions as
the economics of slavery, the authorship of the Federalist Papers and the
question of the existence of God. But what about historical and religious
attributions associated with information gathered from archeological finds? In
1980, a construction crew working in the Jerusalem neighborhood of East Talpiot
stumbled upon a crypt. Archaeologists from the Israel Antiquities Authority
came to the scene and found 10 limestone burial boxes, known as ossuaries, in
the crypt. Six of these had inscriptions. The remains found in the ossuaries
were reburied, as required by Jewish religious tradition, and the ossuaries
were catalogued and stored in a warehouse. The inscriptions on the ossuaries
were catalogued and published by Rahmani (1994) and by Kloner (1996) but there
reports did not receive widespread public attention. Fast forward to March
2007, when a television ``docudrama'' aired on The Discovery Channel entitled
``The Lost Tomb of Jesus'' touched off a public and religious controversy--one
only need think about the title to see why there might be a controversy! The
program, and a simultaneously published book [Jacobovici and Pellegrino
(2007)], described the ``rediscovery'' of the East Talpiot archeological find
and they presented interpretations of the ossuary inscriptions from a number of
perspectives. Among these was a statistical calculation attributed to the
statistician Andrey Feuerverger: ``that the odds that all six names would
appear together in one tomb are 1 in 600, calculated conservatively--or
possibly even as much as one in one million.''Comment: Published in at http://dx.doi.org/10.1214/08-AOAS162 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
The William Kruskal Legacy: 1919--2005
William Kruskal (Bill) was a distinguished statistician who spent virtually
his entire professional career at the University of Chicago, and who had a
lasting impact on the Institute of Mathematical Statistics and on the field of
statistics more broadly, as well as on many who came in contact with him. Bill
passed away last April following an extended illness, and on May 19, 2005, the
University of Chicago held a memorial service at which several of Bill's
colleagues and collaborators spoke along with members of his family and other
friends. This biography and the accompanying commentaries derive in part from
brief presentations on that occasion, along with recollections and input from
several others. Bill was known personally to most of an older generation of
statisticians as an editor and as an intellectual and professional leader. In
1994, Statistical Science published an interview by Sandy Zabell (Vol. 9,
285--303) in which Bill looked back on selected events in his professional
life. One of the purposes of the present biography and accompanying
commentaries is to reintroduce him to old friends and to introduce him for the
first time to new generations of statisticians who never had an opportunity to
interact with him and to fall under his influence.Comment: This paper discussed in: [arXiv:0710.5072], [arXiv:0710.5074],
[arXiv:0710.5077], [arXiv:0710.5079], [arXiv:0710.5081], [arXiv:0710.5084]
and [arXiv:0710.5085]. Published in at
http://dx.doi.org/10.1214/088342306000000420 the Statistical Science
(http://www.imstat.org/sts/) by the Institute of Mathematical Statistics
(http://www.imstat.org
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